While the blood brain barrier has long been considered the crucial interface for therapeutic efficacy within the CNS, more recently poor distribution of agents within the brain itself has emerged as a major delivery challenge. See Arifin, et al. Pharm Res 26, 2289 (2009), Bobo et al., Proc Natl Acad Sci USA 91, 2076 (1994), Kunwar et al., Neuro Oncol 12, 871 (2010), Kunwar et al., J Clin Oncol 25, 837 (2007), Rosso et al., Cancer Res 69, 120 (2009), and Sampson et al., J Neurosurg 113, 301 (2010).
The extracellular space (ECS) in the brain represents the major pathway for movement of many signaling molecules and metabolites as well as therapeutic and diagnostic substances. This space between cells comprises 15-20% of the total brain volume, contains charged and hydrophobic regions, and shifts with changes in cerebral metabolic activity, blood flow, and spinal fluid dynamics. Importantly, the ECS may be more complex in certain pathogenic states, such as intrinsic invasive brain tumors.
It was previously believed that only neutral or negatively charged substances ≤40 nm in diameter could passively diffuse through the brain ECS. See Xiao, et al. Biophys J 95, 1382 (2008); Thorne, et al Proc Natl Acad Sci USA 103, 5567 (2006). For substances with few adhesive interactions, this size is large enough to allow diffusion of nanoparticles, but too small to allow efficient penetration of many particulate drug delivery systems and viruses carrying therapeutic genes. Thus, the brain ECS poses a formidable barrier to therapy with some of the most advanced new treatment modalities.
Passive movements of neurotransmitters, cytokines, chemokines, nutrients, and metabolites are critical to brain function. This movement is regulated in part by the multifaceted extracellular environment in the brain. The diffusion of various substances in the brain extracellular space (ECS) has been studied extensively. A key factor and limitation to diffusion is the ‘mesh spacing’ or ‘pore size’ within the brain ECS.
Understanding the microstructure and mesh spacing of the brain microenvironment has important implications for development of therapeutic and diagnostic nanoparticles, as movement through this space is critical for effective distribution and/or targeting. Numerous studies have estimated the brain ECS mesh size, with early efforts focused on electron microscopy to directly measure structures and spaces in fixed or frozen tissues (Cragg B (1980) Tissue Cell 12(1):63-72; Pappas G D & Purpura D P (1966) Nature 210(5043):1391-1392). This data has been criticized for poor preservation of the tissue architecture and therefore, artifactual results (Cragg 1980; Van Harreveld A & Trubatch J (1979) J Microsc 115(3):243-256). More recently, confocal and multi-photon microscopy have been used to measure the movement of fluorescent molecules or particles in brain slices as well as the cortical surface in vivo. From the fluorescent spread data, the apparent diffusion coefficients for the fluorescent probes were calculated and, from this, ECS mesh spacing was estimated.
While these models reduce the problems inherent to EM measurements, the modeling calculations based on gross particle spread and Fick's Law cannot resolve or analyze trajectories of individual particles and, therefore, are unable to assess micro-rheology, anisotropy, and small-scale Brownian motion. In addition, these methods do not account for bulk flow phenomenon or convective forces introduced by the injection process.
Measurement of the brain ECS pore size has proven to be challenging. Artifacts introduced with tissue preservation and processing as well as the structural heterogeneity of the tissue including anisotropic, electro-statically charged regions and dead-space micro-domains, make many measurements unreliable. Importantly, this space in the living brain is not a static medium. There is continuous cerebral spinal fluid (CSF) bulk flow as well as relative volume fraction and tortuosity changes resulting from cell volume changes in response to varying levels of metabolic activity and anesthetic drugs Sykova et al. Physiol Rev 88(4):1277-1340 (2008), Thorne 2006; Bundgaard et al. J Neurosurg Anesthesiol 13(3):195-201 (2001); Holtmaat et al. Nat Protoc 4(8):1128-1144 (2009); Langsjo et al. Anesthesiology 99(3):614-623 (2003); Nimkoff et al. J Crit Care 12(3):132-136 (1997); Schwedler et al. Can Anaesth Soc J 29(3):222-226 (1982); Szulczyk et al. Acta Physiol Pol 27(1):1-8 (1976). Current data suggests the average mesh spacing to be ≤40 nm, based on the spread of fluorescent probes in the living rat brain (Thorne 2006 and Xiao 2008). While this represents a significant improvement from the earlier EM-based methods, these calculations did not account for convective and bulk flow forces, anesthetic-induced changes, tissue anisotropy, or potential adhesive interactions with the experimental probes.
Moreover, it was believed that a negative or neutral surface charge would enable less interaction and improved diffusion in the brain (Sykova E & Nicholson C (2008) Physiol Rev 88(4):1277-1340; Allard (2009) Biomaterials 30(12):2302-2318). In the 2006 study by Thorne and Nicholson, Proc Natl Acad Sci USA 103(14):5567-5572, PEG-coated quantum dots approximately 35 nm in size with net negative surface charge were used. It is possible that the upper pore size limit set by hindered diffusion of these larger particles was due to hydrophobic and/or electrostatic interactions (surface chemistry) and not steric (size) considerations.
It is therefore an object of the present invention to provide detailed analysis and characterization of the brain tissue, especially of the ECS pore size, as well as the role of surface charge and hydrophobicity/hydrophilicity on and particle penetration in, and drug delivery to, the brain.
It is a further object of the present invention to use this information to provide the particle characteristics that enable maximum drug loading and release times for delivery of therapeutic, prophylactic and diagnostic agents to the brain, while optimizing or maximizing penetration.